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  • Publication
    Design Principles for Boundary Spanning in Transdisciplinary Design Science Research
    ( 2022) ;
    Kruse, L.C.
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    Schoormann, T.
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    Design principles capture prescriptive design knowledge to guide design science researchers and design professionals in their design works. In the context of a transdisciplinary team, design principles can also be a powerful vehicle to bridge knowledge barriers and facilitate collaboration among team members with different backgrounds and expertise. These heterogeneous actors use design principles as a boundary object which helps to mediate their diverse perspectives. The paper draws from boundary object theory to explore the goals and the mechanisms of boundary spanning through ‘design principles-in-use’ and ‘design principles-in-formulation’. We discuss the applicability of our findings using a case of formulation and application of design principles for data spaces in a transdisciplinary research consortium. Our results add the layers of transdisciplinary collaboration to the ongoing discourse on design principles and design knowledge accumulation and evolution.
  • Publication
    Dihedron Algebraic Embeddings for Spatio-Temporal Knowledge Graph Completion
    ( 2022)
    Nayyeri, M.
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    Vahdati, S.
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    Khan, M.T.
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    Alam, M.M.
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    Wenige, L.
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    Behrend, A.
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    Many knowledge graphs (KG) contain spatial and temporal information. Most KG embedding models follow triple-based representation and often neglect the simultaneous consideration of the spatial and temporal aspects. Encoding such higher dimensional knowledge necessitates the consideration of true algebraic and geometric aspects. Hypercomplex algebra provides the foundation of a well defined mathematical system among which the Dihedron algebra with its rich framework is suitable to handle multidimensional knowledge. In this paper, we propose an embedding model that uses Dihedron algebra for learning such spatial and temporal aspects. The evaluation results show that our model performs significantly better than other adapted models.
  • Publication
    Recent Developments in Open Source Simulation Software pandapower and pandapipes
    ( 2022) ;
    Banerjee, Gourab
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    Drauz, Simon Ruben
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    Liu, Zheng
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    Majidi, Maryam
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    ; ;
    We introduce recent developments in the open source Python libraries pandapower and pandapipes. The purpose of pandapower is to provide an easy to use tool for power system analysis and enable a high degree of workflow automation. We describe the recent developments that extend the functionality of pandapower, such as new elements and controllers, as well as the calculation methods for state estimation, distributed slack, short circuit, asymmetric power flow, as well as advanced optimization functions via a new interface to the PowerModels.jl library. Furthermore, we describe the recent progress in the library pandapipes, which provides functionality to simulate pipe networks, such as district heating or gas networks. We demonstrate the new features of pandapipes in an example for transient temperature calculation and showcase the combined application of pandapower and pandapipes to model sector coupling.
  • Publication
    Comparison of Three-Level Grid-Forming Inverter Topologies for Unbalanced and Nonlinear Load Conditions in Microgrids
    Energy production in microgrids is more and more driven by distributed energy sources like photovoltaic, wind or battery systems, replacing diesel generators. For this purpose, inverters are needed that can serve load balancing and reactive power provision. This paper investigates two three-level topologies for grid-forming inverters for such applications with regard to the DC link voltage dimensioning. For the dimensioning of the DC link capacitors, an analytical solution approach for operation at active power is presented. The dimensioning of the capacitors for reactive power operation is determined by a numerical solution in the form of a circuit simulation. The efficiency of the two topologies investigated is compared based on the simulated semiconductor losses. Finally the simulation results of the DC voltage link deviation are compared for one operating point with measurement results of an inverter prototype.
  • Publication
    Analysis of interventions to optimize a pumping process in food production
    ( 2022)
    Colombo, Michael
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    Jell, Philipp
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    Heim, Albert
    In this work in progress report we show the use of Causal Inference with a Double Machine Learning approach to derive recommendations to favorably intervene in a pumping process in food production. At this point the machine learning does not yield statistically significant results due to lack of sufficient data. We further look into strata we have built from the data to study treatment effects but are again limited by the amount of data available. An outline how we intend to proceed with the work is given.